IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v24y2010i9p1903-1924.html
   My bibliography  Save this article

Multiscale Effects on Spatial Variability Metrics in Global Water Resources Data

Author

Listed:
  • Shama Perveen
  • L. James

Abstract

Spatial scales and methods for dealing with scale have been widely discussed in the water resources literature. Different spatial processes operate at different scales so interpretations based on data from one scale may not apply to another. Understanding the behavior of phenomena at multiple-scales of data aggregation is thus imperative to accurate integrations of data and models at different geographic resolutions. This study tests theoretical concepts of scale by presenting empirical results of multiscale GIS and statistical analyses on gridded water-availability, water use and population data for the Danube Basin in Europe, with results corroborated by similar tests in the Ganges (South Asia) and Missouri (North America) Basins. Fine-resolution datasets were aggregated to coarser grid sizes and standard statistical measures of spatial variability were computed. Statistical analysis of spatial variability demonstrated two distinctly different cases for unscaled and scaled variables. Results show that variance (and standard deviation) in unscaled variables like freshwater supply, use and population increases at coarser scales—contrary to the common assumption of decreasing variability as grid-cell size increases. On the other hand, a decreasing trend in variability with scale is noted for variables scaled to area or population (like population density, water availability per capita etc.). Moreover, relationships between variability and scale show strong non-linear trends. No mention of these relationships has been found in the water resources or socio-economic literature for scale and variability. Regression analyses suggest that power functions are the most appropriate model to fit trends in increasing variability at multiple scales. These results can be applied to interpretations of water-stress and water scarcity data and their locations relative to water sources or topographic barriers. Copyright Springer Science+Business Media B.V. 2010

Suggested Citation

  • Shama Perveen & L. James, 2010. "Multiscale Effects on Spatial Variability Metrics in Global Water Resources Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(9), pages 1903-1924, July.
    • Handle: RePEc:spr:waterr:v:24:y:2010:i:9:p:1903-1924
    DOI: 10.1007/s11269-009-9530-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-009-9530-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11269-009-9530-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    2. Surendra Kulshreshtha, 1998. "A Global Outlook for Water Resources to the Year 2025," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 12(3), pages 167-184, June.
    3. S. V. Ciriacy-Wantrup, 1959. "Philosophy and Objectives of Watershed Development," Land Economics, University of Wisconsin Press, vol. 35(3), pages 211-221.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Davy Vanham & Stefanie Millinger & Harald Pliessnig & Wolfgang Rauch, 2011. "Rasterised Water Demands: Methodology for Their Assessment and Possible Applications," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(13), pages 3301-3320, October.
    2. Zhang, Chunxiao & Chen, Min & Li, Rongrong & Fang, Chaoyang & Lin, Hui, 2016. "What's going on about geo-process modeling in virtual geographic environments (VGEs)," Ecological Modelling, Elsevier, vol. 319(C), pages 147-154.
    3. A. Chavez-Jimenez & B. Lama & L. Garrote & F. Martin-Carrasco & A. Sordo-Ward & L. Mediero, 2013. "Characterisation of the Sensitivity of Water Resources Systems to Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(12), pages 4237-4258, September.
    4. Zafar Hussain & Zongmin Wang & Jiaxue Wang & Haibo Yang & Muhammad Arfan & Daniyal Hassan & Wusen Wang & Muhammad Imran Azam & Muhammad Faisal, 2022. "A comparative Appraisal of Classical and Holistic Water Scarcity Indicators," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(3), pages 931-950, February.
    5. Liem Tran & Robert O’Neill & Elizabeth Smith & Randall Bruins & Carol Harden, 2013. "Application of Hierarchy Theory to Cross-Scale Hydrologic Modeling of Nutrient Loads," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1601-1617, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stevanovic Dalibor, 2016. "Common time variation of parameters in reduced-form macroeconomic models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(2), pages 159-183, April.
    2. Wenqing Chen & Melvyn Sim & Jie Sun & Chung-Piaw Teo, 2010. "From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization," Operations Research, INFORMS, vol. 58(2), pages 470-485, April.
    3. A. Fadlelmawla & M. Al-Otaibi, 2005. "Analysis of the Water Resources Status in Kuwait," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(5), pages 555-570, October.
    4. Stefan Mišković, 2017. "A VNS-LP algorithm for the robust dynamic maximal covering location problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1011-1033, October.
    5. Duan, Jinyun & Li, Chenwei & Xu, Yue & Wu, Chia-Huei, 2017. "Transformational leadership and employee voice behavior: a Pygmalion mechanism," LSE Research Online Documents on Economics 68035, London School of Economics and Political Science, LSE Library.
    6. Hota, Monali & Bartsch, Fabian, 2019. "Consumer socialization in childhood and adolescence: Impact of psychological development and family structure," Journal of Business Research, Elsevier, vol. 105(C), pages 11-20.
    7. Abernethy, Margaret A. & Vagnoni, Emidia, 2004. "Power, organization design and managerial behaviour," Accounting, Organizations and Society, Elsevier, vol. 29(3-4), pages 207-225.
    8. Minjiao Zhang & Simge Küçükyavuz & Saumya Goel, 2014. "A Branch-and-Cut Method for Dynamic Decision Making Under Joint Chance Constraints," Management Science, INFORMS, vol. 60(5), pages 1317-1333, May.
    9. Peter Burnell, 2008. "From Evaluating Democracy Assistance to Appraising Democracy Promotion," Political Studies, Political Studies Association, vol. 56(2), pages 414-434, June.
    10. M. J. Naderi & M. S. Pishvaee, 2017. "Robust bi-objective macroscopic municipal water supply network redesign and rehabilitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2689-2711, July.
    11. Mammassis, Constantinos S. & Kostopoulos, Konstantinos C., 2019. "CEO goal orientations, environmental dynamism and organizational ambidexterity: An investigation in SMEs," European Management Journal, Elsevier, vol. 37(5), pages 577-588.
    12. Minghe Sun, 2005. "Warm-Start Routines for Solving Augmented Weighted Tchebycheff Network Programs in Multiple-Objective Network Programming," INFORMS Journal on Computing, INFORMS, vol. 17(4), pages 422-437, November.
    13. Viren Swami & Phik-Wern Loo & Adrian Furnham, 2010. "Public Knowledge and Beliefs About Depression Among Urban and Rural Malays in Malaysia," International Journal of Social Psychiatry, , vol. 56(5), pages 480-496, September.
    14. Jugend, Daniel & da Silva, Sérgio Luis & Salgado, Manoel Henrique & Miguel, Paulo Augusto Cauchick, 2016. "Product portfolio management and performance: Evidence from a survey of innovative Brazilian companies," Journal of Business Research, Elsevier, vol. 69(11), pages 5095-5100.
    15. Ruiwei Jiang & Siqian Shen & Yiling Zhang, 2017. "Integer Programming Approaches for Appointment Scheduling with Random No-Shows and Service Durations," Operations Research, INFORMS, vol. 65(6), pages 1638-1656, December.
    16. Mínguez, R. & García-Bertrand, R., 2016. "Robust transmission network expansion planning in energy systems: Improving computational performance," European Journal of Operational Research, Elsevier, vol. 248(1), pages 21-32.
    17. Jenny Carolina Saldana Cortés, 2011. "Programación semidefinida aplicada a problemas de cantidad económica de pedido," Documentos CEDE 8735, Universidad de los Andes, Facultad de Economía, CEDE.
    18. Ian Maitland & Mitsuhiro Umezu, 2006. "An Evaluation of Japan's Stakeholder Capitalism," Journal of Private Enterprise, The Association of Private Enterprise Education, vol. 22(Spring 20), pages 131-164.
    19. Mikhail A. Sokolovskiy & Xavier J. Carton & Boris N. Filyushkin, 2020. "Mathematical Modeling of Vortex Interaction Using a Three-Layer Quasigeostrophic Model. Part 1: Point-Vortex Approach," Mathematics, MDPI, vol. 8(8), pages 1-13, July.
    20. Craig Loschmann & Özge Bilgili & Melissa Siegel, 2019. "Considering the benefits of hosting refugees: evidence of refugee camps influencing local labour market activity and economic welfare in Rwanda," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 9(1), pages 1-23, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:24:y:2010:i:9:p:1903-1924. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.